Wireless operators are overwhelmed by explosive growth of new applications for mobile and wireless devices. Approximately 500 new apps per day are causing significant issues to consumer wireless communication networks and customer satisfaction. Subscribers enthusiastically adopt new functionality as they concurrently complain about limited smartphone battery life and quality of experience. This may be due to certain applications being greedy in draining battery and consuming resources such as CPU, memory, and bandwidth for transmitting and receiving data volume.
Referring to FIG. 1 a conventional data collection and analysis system is illustrated for comparison with the invention disclosed below. A plurality of user devices reports metrics/measures/data collected in packages through a network to a data store which organizes event data into tables known as Facts. Tables which have common dimensions with other tables may be “joined” to create a more complex “rich Fact”. Measures of the resource consumption of various Apps installed on the user devices are extracted from all of the tables. Because not all users have the same Apps, and the usage of each App varies widely, no two Apps exhibit the same activity profile (“activity data”). For example, the number of times it is opened and closed, length of time it is used, the data it sends and receives from the network, the CPU it consumes, the memory it consumes and the battery capacity it consumes. Means, medians, standard deviations, and various statistical results may be obtained from the activity data and reported in tabular or graphical form which report the relative consumption of resources among the Apps. However, because a minority of enthusiastic users may contribute high activity for an application, while others may generate low activity, these reports may not be useful for all purposes. All things being equal, some extremely active applications, activity due to one user or one app, can overwhelm the statistics of other users or another app. Furthermore, an explicit measurement of application resource consumption (battery drain, CPU usage, memory use, tx data, rx data) may not be available.
What is needed is a way to estimate the resource consumption of each App and to identify: 1) for an individual user on a specific device App resource consumption and over consumption relative to other Apps on other devices on a class or group of devices or on all devices in the population and 2) which Apps over consume resources relative to other Apps for the set of all users on a class or group of devices or on all devices in the population.